1. Field of the Invention
This invention relates to an image processing method and apparatus for carrying out image processing on an image of a predetermined frequency band in an original image.
2. Description of the Prior Art
Techniques for obtaining an image signal, which represents an image, carrying out appropriate image processing on the image signal, and then reproducing a visible image by use of the processed image signal have heretofore been known in various fields. For example, in Japanese Unexamined Patent Publication No. 55(1980)-163772, the applicant proposed a method for carrying out frequency emphasis processing, such as unsharp mask processing, on an image signal, such that a visible radiation image may be obtained, which has good image quality and can serve as an effective tool in, particularly, the efficient and accurate diagnosis of an illness. With the frequency processing, an unsharp mask signal is subtracted from an image signal representing an original image, the resulting difference value is multiplied by an emphasis coefficient, and the thus obtained product is added to the image signal. In this manner, predetermined frequency components in the image are emphasized.
A different method for carrying out frequency processing on an image signal has also been proposed. With the proposed frequency processing method, an image is transformed into multi-resolution images by a Fourier transform, a wavelet transform, a sub-band transform, or the like, and the image signal representing the image is thereby decomposed into signals falling within a plurality of different resolutions or frequency bands. Thereafter, of the decomposed signals, a signal falling within a desired frequency band is subjected to predetermined image processing, such as emphasis.
Further, recently in the field of image processing, a novel technique for transforming an image into a multi-resolution space, which is referred to as the Laplacian pyramid technique, has been proposed in, for example, Japanese Unexamined Patent Publication No. 6(1994)-301766. With the proposed Laplacian pyramid technique, mask processing is carried out on the original image by using a mask having characteristics such that it may be approximately represented by a Gaussian function. A sub-sampling operation is then carried out on the resulting image in order to thin out the number of the picture elements to one half along each of two-dimensional directions of the array of the picture elements in the image, and an unsharp image having a size of one-fourth of the size of the original image is thereby obtained. Thereafter, a picture element having a value of 0 is inserted into each of the points on the unsharp image, which were eliminated during the sampling operation, and the image size is thereby restored to the original size. Mask processing is then carried out on the thus obtained image by using the aforesaid mask, and an unsharp image is thereby obtained. The thus obtained unsharp image is subtracted from the original image, and a detail image of a predetermined frequency band of the original image is thereby obtained. This processing is iterated with respect to the obtained unsharp image, and n number of unsharp images having sizes of 1/2.sup.2n of the size of the original image are thereby formed. As described above, the sampling operation is carried out on the image, which has been obtained from the mask processing with the mask having characteristics such that it may be approximately represented by the Gaussian function. Therefore, though the Gaussian filter is actually used, the same processed image as that obtained when a Laplacian filter is used is obtained. Also, in this manner, the images of low frequency bands, which have the sizes of 1/2.sub.2N of the size of the original image are successively obtained from the image of the original image size. Therefore, the group of the images obtained as a result of the processing is referred to as the Laplacian pyramid.
The Laplacian pyramid technique is described in detail in, for example, "Fast Filter Transforms for Image Processing" by Burt P. J., Computer Graphics and Image Processing, Vol. 16, pp. 20-51, 1981; "Fast Computation of the Difference of Low.cndot.Pass Transform" by Growley J. L., Stern R. M., IEEE Trans. on Pattern Analysis and Machine Intelligence, Vol. 6, No. 2, March 1984; "A Theory for Multiresolution Signal Decomposition; The Wavelet Representation" by Mallat S. G., IEEE Trans. on Pattern Analysis and Machine Intelligence, Vol. 11, No. 7, July 1989; "Image Compression by Gabor Expansion" by Ebrahimi T., Kunt M., Optical Engineering, Vol. 30, No. 7, pp. 873-880, July 1991; and "Multiscale Image Contrast Amplification" by Pieter Vuylsteke, Emile Schoeters, SPIE, Vol. 2167, Image Processing (1994), pp. 551-560.
Japanese Unexamined Patent Publication No. 6(1994)-301766 mentioned above discloses a method, wherein processing for emphasizing image values is carried out on the images of all of the frequency bands in the Laplacian pyramid, which images have been obtained in the manner described above, and the image of each frequency band, which has been obtained from the emphasis processing, is then subjected to an inverse transform, and a processed image is thereby obtained. In the image obtained from such processing, the image has been emphasized in each frequency band. Therefore, an image is obtained such that unsharp mask processing might have been carried out substantially with masks having a plurality of sizes in the aforesaid unsharp mask processing.
Also, "Multiscale Image Contrast Amplification" mentioned above discloses a method comprising the steps of: (i) carrying out processing for multiplying the density of the lowest resolution image, which has the lowest resolution among the images having been decomposed with the Laplacian pyramid technique into a plurality of different frequency bands, by a factor of a (a&lt;1), and (ii) carrying out an inverse multi-resolution transform on the lowest resolution image, which has been obtained from the processing, and the images of the other frequency bands, a processed image being thereby obtained. With the disclosed method, the contrast of the lowest resolution image is restricted, and the processed image can be obtained such that portions of the image covering a wide range of image density can be used. Therefore, it is possible to obtain substantially the same processed image as that obtained when a dynamic range compressing process is carried out on the original image.
However, with the method disclosed in "Multiscale Image Contrast Amplification" mentioned above, the image of the lowest frequency band is merely multiplied by a factor of a, and therefore all of the signal values of the image of the lowest frequency band are processed equally. Therefore, the image information of a signal range, which it is not necessary to process, in the image of the lowest frequency band is processed together with the image information which is to be processed. Accordingly, the degree of freedom of image processing cannot be kept high, and a processed image having a desired quality cannot be obtained. For example, in cases where processing is carried out on a radiation image of the chest of a human body, if the processing described in "Multiscale Image Contrast Amplification" mentioned above is carried out on the image of the lowest frequency band such that the change in density in the mediastinum region may become perceptible, the mediastinum region will become perceptible, but the lung field regions having a high density will be affected adversely. As a result, the thus obtained image will become imperceptible as a whole.